scholarly journals The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

2013 ◽  
Vol 13 (3) ◽  
pp. 6295-6378 ◽  
Author(s):  
L. A. Lee ◽  
K. J. Pringle ◽  
C. L. Reddington ◽  
G. W. Mann ◽  
P. Stier ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Expert Elicitation ◽  
Model Parameters ◽  
Condensation Nuclei ◽  
Model Simulations ◽  
Aerosol Cloud ◽  
Aerosol Emission ◽  
Combustion Particles ◽  
Uncertainty Space ◽  
The Mean

Abstract. The global distribution of cloud condensation nuclei (CCN) is the fundamental quantity that determines how changes in aerosols affect climate through changes in cloud drop concentrations, cloud albedo and precipitation. Aerosol-cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day CCN concentrations. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each monthly-mean model grid cell from an ensemble of 168 one-year model simulations covering the uncertainty space of the 28 parameters. The standard deviation around the mean CCN varies globally between about ±30% of the mean over some marine regions to ±40–100% over most land areas and high latitudes. The results imply that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol-cloud effects on climate. Variance decomposition enables the importance of the parameters for CCN uncertainty to be quantified and ranked from local to global scales. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulphate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulphur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulphate formation during cloud-processing. Most of the 28 parameters are important for CCN uncertainty somewhere on the globe. The results lead to several recommendations for research that would result in improved modelling of cloud-active aerosol on a global scale.

scholarly journals The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

2013 ◽  
Vol 13 (17) ◽  
pp. 8879-8914 ◽  
Author(s):  
L. A. Lee ◽  
K. J. Pringle ◽  
C. L. Reddington ◽  
G. W. Mann ◽  
P. Stier ◽  
...  
Keyword(s):  
Climate Models ◽  
Cloud Condensation Nuclei ◽  
Grid Cell ◽  
Expert Elicitation ◽  
Model Parameters ◽  
Condensation Nuclei ◽  
Model Simulations ◽  
Aerosol Cloud ◽  
Aerosol Emission ◽  
Combustion Particles

Abstract. Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN). Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

A study on aerosol-cloud condensation nuclei (CCN) activation over eastern Himalaya in India

2017 ◽  
Vol 189 ◽  
pp. 69-81 ◽  
Author(s):  
Arindam Roy ◽  
Abhijit Chatterjee ◽  
Chirantan Sarkar ◽  
Sanat Kumar Das ◽  
Sanjay Kumar Ghosh ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Eastern Himalaya ◽  
Condensation Nuclei ◽  
Aerosol Cloud

scholarly journals Incorporation of advanced aerosol activation treatments into CESM/CAM5: model evaluation and impacts on aerosol indirect effects

2014 ◽  
Vol 14 (14) ◽  
pp. 7485-7497 ◽  
Author(s):  
B. Gantt ◽  
J. He ◽  
X. Zhang ◽  
Y. Zhang ◽  
A. Nenes
Keyword(s):  
Indirect Effects ◽  
Radiative Forcing ◽  
Cloud Condensation Nuclei ◽  
Condensation Nuclei ◽  
Activation Kinetics ◽  
Aerosol Cloud ◽  
Model Version ◽  
Cloud Properties ◽  
Aerosol Cloud Interactions ◽  
Aerosol Activation

Abstract. One of the greatest sources of uncertainty in the science of anthropogenic climate change is from aerosol–cloud interactions. The activation of aerosols into cloud droplets is a direct microphysical linkage between aerosols and clouds; parameterizations of this process link aerosol with cloud condensation nuclei (CCN) and the resulting indirect effects. Small differences between parameterizations can have a large impact on the spatiotemporal distributions of activated aerosols and the resulting cloud properties. In this work, we incorporate a series of aerosol activation schemes into the Community Atmosphere Model version 5.1.1 within the Community Earth System Model version 1.0.5 (CESM/CAM5) which include factors such as insoluble aerosol adsorption and giant cloud condensation nuclei (CCN) activation kinetics to understand their individual impacts on global-scale cloud droplet number concentration (CDNC). Compared to the existing activation scheme in CESM/CAM5, this series of activation schemes increase the computation time by ~10% but leads to predicted CDNC in better agreement with satellite-derived/in situ values in many regions with high CDNC but in worse agreement for some regions with low CDNC. Large percentage changes in predicted CDNC occur over desert and oceanic regions, owing to the enhanced activation of dust from insoluble aerosol adsorption and reduced activation of sea spray aerosol after accounting for giant CCN activation kinetics. Comparison of CESM/CAM5 predictions against satellite-derived cloud optical thickness and liquid water path shows that the updated activation schemes generally improve the low biases. Globally, the incorporation of all updated schemes leads to an average increase in column CDNC of 150% and an increase (more negative) in shortwave cloud forcing of 12%. With the improvement of model-predicted CDNCs and better agreement with most satellite-derived cloud properties in many regions, the inclusion of these aerosol activation processes should result in better predictions of radiative forcing from aerosol–cloud interactions.

scholarly journals New particle formation events observed at King Sejong Station, Antarctic Peninsula – Part 1: Physical characteristics and contribution to cloud condensation nuclei

2018 ◽  
Author(s):  
Jaeseok Kim ◽  
Young Jun Yoon ◽  
Yeontae Gim ◽  
Jin Hee Choi ◽  
Hyo Jin Kang ◽  
...  
Keyword(s):  
Antarctic Peninsula ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Particle Formation ◽  
Physical Characteristics ◽  
Weddell Sea ◽  
New Particle Formation ◽  
Condensation Nuclei ◽  
Source Rate ◽  
The Mean

Abstract. The physical characteristics of aerosol particles during a particle burst observed at King Sejong Station in Antarctic Peninsula from March 2009 to December 2016 were analyzed. This study focuses on the seasonal variation in parameters related to particle formation such as the occurrence, formation rate (FR) and growth rate (GR), condensation sink (CS), and source rate of condensable vapor. The number concentrations during new particle formation (NPF) events varied from 1707 cm−3 to 83 120 cm−3, with an average of 20 649 ± 9290 cm−3, and the duration of the NPF events ranged from 0.6 h to 14.4 h, with a mean of 4.6 ± 1.5 h. The NPF event dominantly occurred during austral summer period (~ 72 %). The mean values of FR and GR of the aerosol particles were 2.79 ± 1.05 cm−3 s−1 and 0.68 ± 0.27 nm h−1, respectively showing enhanced rates in the summer season. The mean value of FR at King Sejong Station was higher than that at other sites in Antarctica, at 0.002–0.3 cm−3 s−1, while those of growth rates was relatively similar results observed by precious studies, at 0.4~4.3 nm h−1. The average values of CS and source rate of condensable vapor were (6.04 ± 2.74) × 10−3 s−1 and (5.19 ± 3.51) × 104 cm−3 s−1, respectively. The contribution of particle formation to cloud condensation nuclei (CCN) concentration was also investigated. The CCN concentration during the NPF period increased approximately 9 % compared with the background concentration. In addition, the effects of the origin and pathway of air masses on the characteristics of aerosol particles during a NPF event were determined. The FRs were similar regardless of the origin and pathway, whereas the GRs of particles originating from the Antarctic Peninsula and the Bellingshausen Sea, at 0.77 ± 0.25 nm h−1 and 0.76 ± 0.30 nm h−1, respectively, were higher than those of particles originating from the Weddell Sea (0.41 ± 0.15 nm h−1).

scholarly journals Bacteria as Cloud Condensation Nuclei (CCN) in the Atmosphere

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 786
Author(s):  
Mihalis Lazaridis
Keyword(s):  
Contact Angle ◽  
Sulfuric Acid ◽  
Cloud Condensation Nuclei ◽  
Sulfuric Acid Concentration ◽  
Contact Angles ◽  
Nucleation Theory ◽  
Classical Nucleation Theory ◽  
Condensation Nuclei ◽  
Critical Cluster ◽  
Model Simulations

Bacteria activation and cloud condensation nuclei (CCN) formation have been studied in the atmosphere using the classical theory of heterogeneous nucleation. Simulations were performed for the binary system of sulfuric acid/water using laboratory-determined contact angles. Realistic model simulations were performed at different atmospheric heights for a set of 140 different bacteria. Model simulations showed that bacteria activation is a potentially favorable process in the atmosphere which may be enhanced at lower temperatures. CCN formation from bacteria nuclei is dependent on ambient atmospheric conditions (temperature, relative humidity), bacteria size, and sulfuric acid concentration. Furthermore, a critical parameter for the determination of bacteria activation is the value of the intermolecular potential between the bacteria’s surface and the critical cluster formed at their surface. In the classical nucleation theory, this is parameterized with the contact angle between substrate and critical cluster. Therefore, the dataset of laboratory values for the contact angle of water on different bacteria substrates needs to be enriched for realistic simulations of bacteria activation in the atmosphere.

scholarly journals The challenge of simulating the sensitivity of the Amazonian clouds microstructure to cloud condensation nuclei number concentrations

2019 ◽  
Author(s):  
Pascal Polonik ◽  
Christoph Knote ◽  
Tobias Zinner ◽  
Florian Ewald ◽  
Tobias Kölling ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Cloud Base ◽  
Condensation Nuclei ◽  
Aerosol Cloud ◽  
Microphysical Properties

Abstract. The realistic representation of cloud-aerosol interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon area has been one of the motivations for several field observations, including the airborne Aerosol, Cloud, Precipitation, and Radiation Interactions and DynamIcs of CONvective cloud systems – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA) campaign based in Manaus, Brazil in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysical properties (droplet number concentration and effective radius). We found agreement between modeled and observed median cloud droplet number concentrations (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of two was found, which means a systematic underestimation of modeled CDNC as compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations and cloud droplet effective radii (reff) was also underestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN per cm3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Regional background aerosol concentrations were sufficiently high such that the additional CCN emitted from local fires did not cause a notable change in modelled cloud microphysical properties. In addition, we evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedo effect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm−3.

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